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Work Performed for Recent Clients (at their facilities):

                                    

Arête Associates-Crystal City, Virginia (local office had been located in Wakefield, MA):
Developed a Kalman filter-based covariance analysis program in MatLab® and exercised it by performing quantitative analyses of the relative pointing accuracy associated with each of several alternative candidate INS platforms of varying gyro drift-rate quality (and cost) by using high quality GPS external position and velocity fix alternatives: (1) P(Y)-code, (2) differential mode, or (3) kinematic mode at  higher rates to enhance the INS with frequent updates to compensate for gyro drift degradations that otherwise adversely increase in magnitude and severity to the system as time elapses. 
 
Raytheon-Sudbury, Massachusetts:
Provided analysis and tracking related sections  of Software Requirements Specification (SRS) for RUV EKF, RVCC EKF, Maximum Likelihood Least Squares Batch Algorithm, and Track Initiation based on the Lambert Algorithm for Updated Early  Warning Radar (UEWR) as part of National Missile Defense (NMD). Also looked into Interactive Multiple Model (IMM) Kalman filters for UEWR.

     1. Kerr, T. H., and Satz, H. S., Evaluation of Batch Filter Behavior in comparison to EKF, TeK Associates, Lexington, MA, (for Raytheon, Sudbury, MA), 22 Nov. 1999.

      2. Kerr, T. H., TeK Associates view in comparing use of a recursive Extended Kalman Filter (EKF) versus use of Batch Least Squares (BLS) algorithm for UEWR, TeK Associates, Lexington, MA, (for Raytheon, Sudbury, MA), 12 Sep. 2000.

      3. Kerr, T. H., Considerations in whether to use Marquardt Nonlinear Least Squares vs. Lambert Algorithm for NMD Cue Track Initiation (TI) Calculations, TeK Associates Technical Report No. 2000-101, Lexington, MA, (for Raytheon, Sudbury, MA), 27 Sep. 2000. [Prior to the existence of the Wikipedia article, appearing as a link at the end of the present discussion on this Web Site, which does describe the particular Levenberg-Marquardt algorithm of interest and which finally identifies where it was actually published in the prior open literature, NMD analysts at XonTech and elsewhere working on NMD had the correct computer code and used it properly but did not have the corresponding documentation or rationale for the correctness of this particular algorithm because they relied entirely on what was cited in the W. H. Press books, which both referenced the wrong documentation of the particular Levenberg-Marquardt algorithm of interest although the write-up cited was in fact by the same author Donald Marquardt but, unfortunately, did not correspond to the specific Levenberg-Marquardt algorithm. The correct documentation describing the Levenberg-Marquardt Least Squares curve fitting algorithm invoked for use as computer code within the 1986 Cambridge University Press book by William Vetterling, Saul Teukolsky, William Press, and Brian Flannery entitled Numerical -Example Book (FORTRAN), pp. 197-209 is found elsewhere. The correct rationale is published in Marquardt, D., An Algorithm for Least Squares Estimation of Nonlinear Parameters, SIAM Journal of Applied Mathematics, Vol. 11, 1963. The same problem of citing the wrong publication occurs within Press, W. H., Teukolsky, S. A., et al, Numerical Recipes: The Art of Scientific Computing, Cambridge University Press, NY, 1992, (2nd Edition) 1996, (3rd Edition) 2007 [the document citation occurred as comment lines directly within the computer source code associated with these books authored by W. H. Press]. The behavior of the Levenberg-Marquardt algorithm (apparently developed earlier by Levenberg in 1944 and rediscovered by Donald Marquardt, a prominent numerical analyst investigating and developing a variety of optimization algorithms at Dupont Laboratory in the 1960s) is described as interpolating or alternating between the behavior of a Gauss-Newton algorithm and the method of Gradient Descent (or method of Steepest Descent). Kerr was aware, as he wrote the above memo, that the documentation of the algorithm that most NMD analysts were citing did not correspond to the computer code that they were actually using at the time and so the available computer code was not yet acceptable to be included in an SRS for this reason since the rationale was missing. Kerr sought a solution in this memo that would allow all involved to save face, but evidently to his detriment. We at TeK Associates have been aware of the desirability of using the Levenberg-Marquardt algorithm for optimization applications since encountering its use in a parameter identification algorithm at Systems Control, as dicussed in Narendra K. Gupta and Raman K.  Mehra, Computational Aspects of Maximum Likelihood Estimation and Reduction in Sensitivity Function Calculations, IEEE Trans. on Automatic Control, Vol. 19, No. 6, pp. 774-783, Dec. 1974 and within Wally Larimore's alternative maximum likelihood parameter estimation algorithm: “Paraide”, developed later at TASC for the same purpose. Click here for a nice description of this algorithm in Wikipedia.]  Another possible complaint is that this present author did not decide which of the three identified options to choose. As an outside consultant, his job was to identify the options clearly, to put them on a platter for easy viewing by others, and to identify pros and cons of each option. Any reputable consultant knows to not make the decision for the client when the client has that ultimate responsibility. The final decision concerning which to use should be made by an actual employee responsible for their final design (and at that time, Raytheon was the NMD UEWR prime.) They apparently prefer their consultants to merely over describe or overwrite regarding a particular topic such as devoting more than 20 pages to rehash the principles of Matched Filtering, which had already been splendidly explained in half a page in Sakrison, D. J., Communication Theory: Transmission of Waveforms and Digital Information, John Wiley, New York, 1968. One final misunderstanding: Joseph Cynamon, who had retired from Raytheon, but returned later as an outside consultant, came back from a meeting with Roger Reed on a late Friday afternoon and told Tom that Roger had said that Tom should work with Joe in putting a WindowsGUI veneer onto an older DOS-based Raytheon software product that Joe had developed years earlier. Tom worked on it over the weekend on his own time and disseminated the results of his software adaptation on the following Monday morning. Tom was dressed down by Roger Reed right afterwards as not working on what he was assigned to do for Raytheon since Tom had now done this software development that was not asked for by Roger. Roger did not realize that this was just work done over the weekend on Toms own time and Tom had been falsely told by Joe Cynamon that the request came directly from Roger. However, Tom should have gotten the request directly from the horses mouth so to speak, rather than have relied on what Joe Cynamon conveyed since Joe was evidently conveying his own desires and pretending that the changed "marching orders" had come from Roger, Toms handler at Raytheon. The next time, Tom will wait to get it in writing. Evidently, you cant trust anyone. 

      4. Satz, H. S., Kerr, T.  H., Comparison of Batch and Kalman Filtering for Radar Tracking, Proceedings of 10th Annual AIAA/BMDO Conference, Williamsburg, VA, 25 Jul. 2001 (Unclassified, but Conference Proceedings are SECRET).

      5. Participated in the writing of the Software Requirements Specification (SRS) for Raytheons Batch Least Squares (BLS) Algorithm, RVCC EKF, RUV EKF, Interactive Multiple Model (IMM) Filter, and Track Initiation (TI)

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Homeland Missile Defense System Successfully Intercepts ICBM Target:
https://mda.mil/news/19news0003.html?fbclid=IwAR2Cd0jAFPDBcfBZ9A-nQ39dnb5ofOciasbtbqCHsaFDrLCPyUifBT5R7wE 

XonTech-Bedford, Massachusetts (local office relocated to Burlington, MA and eventually acquired by Northrop Grumman in 2003):

Engineering consulting on Extended Kalman Filter (EKF) tracking specifications and alternative algorithms using Cramer-Rao Lower Bound target-tracking accuracy evaluations for Updated Early Warning Radar (UEWR). Authored Tracking Analysis Notebook and responded to action items.

      1. Kerr, T. H., UEWR Design Notebook-Section 2.3: Track Analysis, TeK Associates, Lexington, MA, (for XonTech, Hartwell Rd, Lexington, MA), XonTech Report No. D744- 10300, 29 Mar. 1999.

MITRE-Bedford, Massachusetts:
Engineering consulting on Extended Kalman Filter (EKF) tracking specifications and evaluations of target-tracking accuracy for Updated Early Warning Radar (UEWR) using Cramer-Rao Lower Bound methodology that we implemented in MatLab® and exercised. Used Simulink® for a simple RV trajectory generator.

      1. Kerr, T. H., NMD White Paper on Designated Action Item, MITRE, Bedford, MA, Jan. 1998.

      2. Kerr, T . H., Cramér-Rao Lower Bound Implementation and Analysis for NMD Radar Target Tracking, TeK Associates Technical Report No. 97-101 (for MITRE), Lexington, MA, 26-30 Oct. 1997.

      3. Kerr, T. H., Cramér-Rao Lower Bound Implementation and Analysis: CRLB Target Tracking Evaluation Methodology for NMD Radars, MITRE Technical Report, Contract No. F19628-94-C-0001, Project No. 03984000-N0, Bedford, MA, Feb. 1998.

      4. Kerr, T. H., Developing Cramér-Rao Lower Bounds to Gauge the Effectiveness of UEWR Target Tracking Filters, Proceedings of AIAA/BMDO Technology Readiness Conference and Exhibit, Colorado Springs, CO, 3-7 Aug. 1998.

 
Lincoln Laboratory of MIT-Lexington, Massachusetts:
Engineering analysis of use of GPS fixes as a navaid for updating a LaserNav Inertial Navigation System (INS) during airborne terrain mapping. Refined and simulated an Iterated Extended Kalman Filter (EKF) implementation for RV target  tracking. Became cognizant of standard Reentry Vehicle (RV) countermeasures. Investigated and documented the drawbacks associated with using Neural Networks in control applications.

      1. Kerr, T. H., Emulating Random Process Target Statistics (using MSF), IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-30, No. 2, pp. 556-577, Apr. 1994.

      2. Kerr, T. H., Use of GPS/INS in the Design of Airborne Multisensor Data Collection Missions (for Tuning NN-based ATR algorithms), the Institute of Navigation (ION) Proceedings of GPS-94, Salt Lake City, UT, pp. 1173-1188, 20-23 Sep. 1994.

      3. Kerr, T. H., Assessing and Improving the Status of Existing Angle-Only Tracking (AOT) Results, Proceedings of the International Conference on Signal Processing Applications & Technology (ICSPAT), Boston, MA, pp. 1574-1587, 24-26 Oct. 1995.

      4. Kerr, T. H., A Critique of Neural Networks as Currently Exist for Control and Estimation, Proceedings of the International Conference on Signal Processing Applications & Technology (ICSPAT), Boston, MA, pp. 1434-1443, 24-26 Oct. 1995.

      5. Kerr, T. H., A Critique of Some Neural Network Architectures and Claims for Control and Estimation,IEEE Transactions on Aerospace and Electronic Systems, Vol. 34, No. 2, pp. 406-419, Apr. 1998 (extends beyond prior version above).

Google Books (now defunct):
Thomas H. Kerr III is willing  to do whatever it takes to keep TeK Associates going while completing his companys commercial product: TK-MIP. He has even farmed himself out to work at a miserably low rate to keep things moving forward in a bad U.S. economy (2007-2009). For example, he worked at Google Books on Hartwell Place for those two years (doing manual labor along with 19 and 20 year olds) until Google allowed him to, instead, perform a QA/QC role on the 2-D images. Even that required occasional manual labor. Even though it was for only a two year contract, Google Books in Lexington had a very high turn-over rate back then. Relatively few completed their full two year tour of duty. Google Books had all sorts of target goals (that kept adjusting upwards) and tighter and tighter error criteria that had to be met in order to continue working there. However, the diversity of the work force was great.

OKSI in Torrence, CA: OKSI specification For My Software

GCR for Draper Laboratory: Theory behind Some Covariance Sensitivity Studies 

For Dataalytics:

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=13&cad=rja&uact=8&ved=2ahUKEwja8JLy66TmAhXNwVkKHY_BAr8QFjAMegQIBhAC&url=https%3A%2F%2Fwww.mdpi.com%2F1911-8074%2F12%2F1%2F48%2Fpdf&usg=AOvVaw19l_O1DvzZGT_qSQbu6vyi 

...Several methods are available for the measurement of portfolio risk and we divide them into (a)moment-based risk measurement and (b) moment-based and quantile-based risk measurement. The moment-based methods include time-varying covariance matrix and the shrinkage estimation use the covariance matrix in the risk measurement...

This provided some motivation for the post below:

Covariance Analysis:
https://arxiv.org/pdf/1305.4268.pdf 

Historically (from 1973 until 1992), our customer for:

SSBN submarine SINS/ESGM Navigation and navaid observables studies was Jerry Katz, Strategic Systems Project Office, SP-2413 in Crystal City, VA;

Joint Tactical Information and Distribution System (JTIDS) distributed or decentralized filtering was Lenny Chin (Naval Air Development Center in Warminster, PA);

NAVSAT platform operational testing was Dick Akita, Naval Ocean Systems Center (NOSC) in San Diego, CA;

GPS Reciever characterization and alternative contractor compliance was Dick Akita (NOSC) in San Diego, CA;

GPS Operational Testing onboard Attack Submarines (at Submarine Naval Base in San Diego) was George Lowenstein at NADC;

At Lincoln Laboratory, our customers were BMD (for Group 95) and DARPA (for Group 53).

      To avoid needless duplication, the open literature publications and company technical reports (written for the above 5 historical customers) are listed under the appropriate specialized topic headings appearing within this consulting section, of which this present screen is a subsection.

In more than 40+ years of professional practice, we have never been involved in any legal disputes whatsoever, nor in disputes or involvements relating to any of our professional activities, nor relating to our product outputs. Our outputs have consisted exclusively of written reports for our clients and the associated technical journal papers and conference articles that are in directly related areas. Any subsequent implementation of our ideas into actual weapons systems or in military platforms (i.e., vehicles) is independently performed by others. We are held harmless as a standard stipulation in all of our contracts for engineering analysis services. To be immediately useful and clearly understood by our clients and other readers, our written products are admittedly explicit (i.e., we cut to the chase and avoid  innuendo) and are sometimes somewhat provocative but are always safely backed up with copious independent concrete reference citations and explicit confirming precedents as well as independently repeatable simulations "up the wazoo". As a rule, TeK Associates avoids going out on a limb!

Our publications are frequently cited by other independent authors and researchers; for example:

·        Skog, I., Handel, P., In-Car Positioning and Navigation Technologies-A Survey, IEEE Transactions on Intelligent Transportation Systems, Vol. 10, No. 1, pp. 4-21, Mar. 2009. 

·        Smith, M. A., On Doppler Measurements for Tracking, International Conference on Radar, Adelaide, Australia, Vol. 1 and 2, pp. 309-314, 2-5 Sep. 2008. 

·        Shi, Y., Han, C.  Z., Lian, F., The Iterated divided difference filter, IEEE International Conference on Automation and Logistics, 1-3 Sep. 2008, Qingdao, Peoples Republic of China, Vols. 1-6, pp. 1799-1802, 2008. 

·        Banani, S. A., Masnadi-Shirazi, M. A., A New Version of Unscented Kalman Filter, Proceedings of Conference of the World Academy of Science, Engineering, and Technology, Barcelona, Spain, Vol. 20, pp. 192-197, 25-27 Apr. 2007.

·        Petsios, M. N., Alivizatos, E. G., Uzunoglu, N. K., Solving the association problem for a multistatic range-only radar target tracker, Signal Processing, Vol. 88, No. 9, pp. 2254-2277, Sep. 2008. 

·        Xu, B. L., Chen, Q. L., Wu, Z. Y., et al, Analysis and approximation of performance bound for two-observer bearings-only tracking, Information Sciences, Vol. 178, No. 8, pp. 2059-2078, 15 Apr. 2008. 

·        Hovareshti, P., Gupta, V., Baras, J. S., Sensor scheduling using smart sensors, Proceedings of 46th IEEE Conference on Decision and Control, New Orleans, LA, Vols. 1-14, pp. 6083-6088, 12-14 Dec. 2007.

·        Gadzhiev, C. M., Determining the operating conditions of floating marine platforms based on the predicted motion control under conditions of wind and wave disturbances, Measurement Techniques, Vol. 51, No. 1, pp. 28-33, Jan. 2008.

·        Choudhury, D. R., Shifted power method for positive semidefinite matrices using Gerschgorin, Proceedings of 10th World Multi-Conference on Systemics, Cybernetics and Informatics/12th International Conference on Information Systems Analysis and Synthesis, Orlando, FL, WMSCI 2006, Vol. IV, pp. 251-253, 16-19 Jul. 2006. 

·        Fong, K. F., Loh, A. P., Tan, W. W., A frequency domain approach for fault detection, International Journal of Control, Vol. 81, No. 2, pp. 264-276, 2008. 

·        Xu, B. L., Wu, Z. Y., Wang, Z. Q., Theoretic performance bound for bearings-only tracking, Proceedings of 6th International Conference on Machine Learning and Cybernetics, Hong Kong, Peoples Republic of China, Vols. 1-7, pp. 2300-2305, 19-22 Aug. 2007.

·        Duan, F. Y., Wang, H., Zhang, L. J., et al, Study on fault-tolerant filter algorithm for integrated navigation system, Proceedings of IEEE International Conference on Mechatronics and Automation, 5-8 Aug. 2007, Harbin, Peoples Republic of China, 2007, Vols. I-V, pp. 2419-2423, 2007. 

·        Tong, Z. M., Tang, W. Y., The application of data fusion in optical theodolite coordinate measurement system, art. no. 65951O, Proceedings of Conference on Fundamental Problems of Optoelectronics and Microelectronics III, 12-14 Sep. 2006, Harbin, Peoples Republic of China, Pts. 1 and 2, Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE), Vol. 6595, pp. 5951-5951, Parts 1-2, 2007. 

·        Kramer, K. A., Stubberud, S. C., Geremiam, J. A., Sensor calibration using the neural extended Kalman filter in a control loop, Proceedings of IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, 27-29 Jun. 2007, Ostuni, Italy, pp. 19-24, 2007. 

·        Xu, B. L., Wu, Z. Y., Wang, Z. Q., On the Cramér-Rao lower bound for biased bearings-only maneuvering target tracking, Signal Processing, Vol. 87, No. 12, pp. 3175-3189, Dec. 2007. 

·        Mironovskii, L. A., The use of analytical redundancy in navigational measuring systems, Proceedings of 4th International Seminar on Mathematical, Statistical, and Computer Support of Measurement Quality, 28-30 Jun. 2006, St. Petersburg, Russia, Measurement Techniques, Vol. 50, No. 2, pp. 142-148, Feb. 2007.

·        Li, X. R., Jilkov, V. P., Survey of maneuvering target tracking. Part V: Multiple-model methods,” IEEE Trans. on Aerospace and Electronic Systems, Vol. 41, No. 4, pp. 1255-1321, Oct. 2005. 

·        Li, X. R., Jilkov, V. P., A survey of maneuvering target tracking: Approximation techniques for nonlinear filtering,” 16th Conference on Signal and Data Processing of Small Targets, 13-15 Apr. 2004 Orlando, FL, Signal and Data Processing of Small Targets 2004, Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE), Vol. 5428, pp. 537-550, 2004.

·        Koutsoukos, X. D., Estimation of hybrid systems using discrete sensors,” Proceedings of 42nd IEEE Conference on Decision and Control, Maui, HI, Vols. 1-6, Dec. 09-12, 2003.

·        Rapoport, I., Oshman, Y., A Cramér-Rao type lower bound for the estimation error of systems with measurement faults,” Proceedings of 42nd IEEE Conference on Decision and Control, 9-12 Dec. 2003, Maui, HI, Vols. 1-6, pp. 4853-4858, 2003.

·        Bessell, A., Ristic, B., Farina, A., et al., Error performance bounds for tracking a maneuvering target,” Proceedings of 6th International Conference on Information Fusion, 8-11 Jul. 2003, Cairns, Australia, FUSION 2003, Vols. 1-2, pp. 903-910, 2003. 

·        Xiong, W., He, Y., Zhang, J. W., Centralized multisensor nonlinear filter method,” Proceedings of 3rd International Symposium on Instrumentation Science and Technology, 18-22 Aug. 2004, Xian, People's Republic China, Vol. 2, pp. 526-530, 2004.

·        Ristic, B., Farina, A., Hernandez, M., Cramér-Rao lower bound for tracking multiple targets,” IEE Proceedings-Radar, Sonar, and Navigation, Vol. 151, No. 3, pp. 129-134, Jun. 2004. 

·        Behazin, F., Nabavi, B., Fesharaki, M. N., The reformulation and modification on iterated EKF for applications with large-dimension measurement,” Proceedings of 6th International Conference on Signal Processing, 26-30 Aug. 2002, Beijing, People's Republic of China, Vols. I and II, pp. 756-759, 2002.

·        Simandl, M., Straka, O., Setting sample size in particle filters using Cramér-Rao bound,” Proceedings of 5th IFAC Symposium on Nonlinear Control Systems, 4-6 Jul. 2001, St. Petersburg, Russia, Nonlinear Control Systems 2001, Vols. 1-3, IFAC Symposia Series, pp. 681-686, 2002.

·        Ning, X. L., Fang, J. C., A new method of autonomous navigation for deep space explorer based on information fusion,” Proceedings of 6th International Conference on Electronic Measurement and Instruments, 18-21 Aug. 2003, Taiyuan, People's Republic of China, Vols. 1-3, pp. 220-224, 2003. 

·        Li, X. R., Jilkov, V. P., A survey of maneuvering target tracking - Part II: Ballistic target models,” Proceedings of 13th Conference on Signal and Data Processing of Small Targets, 30 Jul.-2 Aug. 2001, San Diego, CA, Proceedings of The Society of Photo-Optical Instrumentation Engineers (SPIE), Vol. 4473, pp. 559-581, 2001.

·        Li, X. R., Jilkov, V. P., A survey of maneuvering target tracking - Part III: Measurement models,” Proceedings of 13th Conference on Signal and Data Processing of Small Targets, 30 Jul.-2 Aug. 2001, San Diego, CA, Proceedings of The Society of Photo-Optical Instrumentation Engineers (SPIE), Vol. 4473, pp. 423-446, 2001. 

·        Li, X. R., Jilkov, V. P., A survey of maneuvering target tracking - Part IV: Decision-based methods,” Proceedings of 14th Conference on Signal and Data Processing of Small Targets, 2-4 Apr. 2002, Orlando, FL, Proceedings of The Society of Photo-Optical Instrumentation Engineers (SPIE), Vol. 4728, pp. 511-534, 2002. 

·        El-Mahy, M. K., Efficient satellite orbit determination algorithm,” Proceedings of 18th National Radio Science Conference (NRSC 2001), 27-29 Mar. 2001, Mansoura, Egypt, Vols. 1 and 2, pp. 225-232, 2001.

·        Parra-Michel, R., Kontorovitch, V. Y., Orozco-Lugo, A. G., Simulation of wide band channels with nonseparable scattering functions,” Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 13-17 MAY 2002 ORLANDO, FL, Vols. I-IV, pp. 2829-2832, 2002 

·        Hanebeck, U. W. D., Recursive nonlinear set-theoretic estimation based on pseudo ellipsoids,” Proceedings of International Conference on Multisensor Fusion and Integration for Intelligent Systems, 20-22 Aug. 2001, Baden Baden, Germany, pp. 159-164, 2001. 

·        Mosavi, M. R., Mohammadi, K., Improve the position accuracy on low cost GPS receiver with adaptive neural networks,” Proceedings of Student Conference on Research and Development-Globalizing Research and Development in Electrical and Electronics Engineering, 16-17 Jul. 2002, Shah Alam, Malaysia,, pp. 322-325, 2002.

·        Campa, G., Fravolini, M. L., Napolitano, M, et al., Neural networks-based sensor validation for the flight control system of a B777 research model,” Proceedings of 20th Annual American Control Conference (ACC), 8-10 May 2002, Anchorage, AK, Vols. 1-6, pp. 412-417, 2002.

·        Vershinin, Y. A., A data fusion algorithm for multisensor systems,” Proceedings of 5th International Conference on Information Fusion (FUSION 2002), 8-11 Jul. 2002 Annapolis, MD, Vol. I, pp. 341-345, 2002. 

·        Chetouani, Y., Mouhab, N., Cosmao, J. M., et al., Application of extended Kalman filtering to chemical reactor fault detection,” Chemical Engineering Communications, Vol. 189, No. 9, pp. 1222-1241, Sep. 2002. 

·        Stentz, A., Dima, C., Wellington, C., et al., A system for semi-autonomous tractor operations,” Autonomous Robots, Vol. 13, No. 1, pp. 87-104, Jul. 2002. 

·        Carpenter, J. R., Decentralized control of satellite formations,” International Journal of Robust and Nonlinear Control, Vol. 12, No. 2-3, pp. 141-161, Feb.-Mar. 2002. 

·        Mirabadi, A., Mort, N., Schmid, F., A fault tolerant train navigation system using multisensor, multifilter integration techniques,” Proceedings of International Conference on Multisource-Multisensor Information Fusion (FUSION '98), 6-9 Jul. 1998 Las Vegas, NV, Vols. 1 AND 2, pp. 340-347, 1998. 

·        Degen, U., Operations research of tracking algorithms for air surveillance system,” Proceedings of International Conference on Multisource-Multisensor Information Fusion (FUSION '98), 6-9 Jul. 1998 Las Vegas, NV, Vols. 1 and 2, pp. 850-855, 1998.

·        Fravolini, M.L., Campa, G., Napolitano, M., et al., Minimal resource allocating networks for aircraft SFDIA,” Proceedings of IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM '01), 8-12 Jul. 2001, Como, Italy, Vols. I and II, pp. 1251-1256, 2001. 

·        Hasan, K., Hossain, J., Multichannel autoregressive spectral estimation from noisy observations,” Proceedings of 10th International IEEE Tencon Conference, 24-27 Sep. 2000, Kuala Lumpur, Malaysia, Vols. I-III, Intelligent Systems and Technologies for the New Millennium, pp. 327-332, 2000. 

·        Simandl, M., Kralovec, J., Tichavsky, P., Filtering, predictive, and smoothing Cramér-Rao bounds for discrete-time nonlinear dynamic systems,” Proceedings of 14th IFAC World Congress, 5-9 Jul. 1999, Beijing, Peoples Republic of China, Automatica, Vol. 37, No. 11, pp. 1703-1716, Nov. 2001. 

·        Leung, H., Zhu, Z. W., Performance evaluation of EKF-based chaotic synchronization,” IEEE Transactions on Circuits and System I-Fundamental Theory and Applications, Vol. 48, No 9, pp. 1118-1125, Sep. 2001. 

·        Sivananthan, S., Kirubarajan, T., Bar-Shalom, Y., Radar power multiplier for acquisition of low observables using an ESA radar,” IEEE Transactions on Aerospace and Electronic Systems Systems, Vol. 37, No. 2, pp. 401-418, Apr. 2001. 

·        Li, Y., Sundararajan, N., Saratchandran, P., Stable neuro-flight-controller using fully tuned radial basis function neural networks,” Journal of Guidance, Control, and Dynamics, Vol. 24, No. 4, pp. 665-674, Jul.-Aug. 2001. 

·        Niu, R. X., Willett, P., Bar-Shalom, Y., Matrix CRLB scaling due to measurements of uncertain origin,” IEEE Transactions on Signal Processing, Vol. 49, No. 7, pp. 1325-1335, Jul. 2001. 

·        Bergman, N., Doucet, A., Gordon, N., Optimal estimation and Cramér-Rao bounds for partial non-gaussian state space models,” Proceedings of International Symposium on the Frontiers of Time Series Modeling, 14-16 Feb. 2000, Annals of the Institute of Statistical Mathematics, Tokyo, Japan, Vol. 53, No. 1, Special Issue, pp. 97-112, Mar. 2001. 

·        Mahapatra, P. R., Mehrotra, K., Mixed coordinate tracking of generalized maneuvering targets using acceleration and jerk models,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 36, No. 3, pp. 992-1000, Jul. 2000. 

·        Mirabadi, A., Schmid, F., Mort, N., Fault detection and isolation in a multisensor train navigation system,” Proceedings 6th International Conference on Computer Aided Design, Manufacture, and Operation in the Railway and Other Advanced Mass Transit Systems, 2-4 Sep. 1998, Lisbon, Portugal, Computers in Railways VI, Advances in Transportation, Vol. 2, pp. 1025-1035, 1998. 

·        Jayakumar, M., Banavar, R. N., Risk-sensitive filters for recursive estimation of motion from images,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 6, pp. 659-666, Jun. 1998. 

·        Tichavsky, P., Muravchik, C. H., Nehorai, A., Posterior Cramér-Rao bounds for discrete-time nonlinear filtering,” Proceedings of 1st European Conference on Signal Analysis and Prediction (ECSAP-97), 24-27 Jun. 1997 Prague, Czech Republic, IEEE Transactions on Signal Processing, Vol. 46, No. 5, pp. 1386-1396, May 1998. 

·        Koshaev, D. A., A comparison of lower bounds of accuracy in problems of nonlinear estimation,” Journal of Computer and Systems Sciences International, Vol. 37, No. 2, pp. 222-225, Mar.-Apr. 1998. 

·        Mazor, E., Averbuch, A., Bar-Shalom, Y., et al., Interacting multiple model methods in target tracking: A survey,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 34, No. 1, pp. 103-123, Jan. 1998. 

·        Koshaev, D. A., Stepanov, O. A., Application of the Rao-Cramér inequality in problems of nonlinear estimation,” Journal of Computer and System Sciences International, Vol. 36, No. 2, pp. 220-227, Mar.-Apr. 1997. 

·        on page 208 in Bevly, D. M., Parkinson, B., Cascaded Kalman Filters for Accurate Estimation of Multiple Biases, Dead-Reckoning Navigation, and Full State Feedback Control of Ground Vehicles, IEEE Trans. on Control Systems Technology, Vol. 15, No. 2, pp. 199-208, Mar. 2007.

·        Ristic, B., “Cramér Rao Bounds for Target Tracking,International Conference on Sensor Networks and Information Processing, 6 Dec. 2005.

·        on page 81 of Ristic, B., Arulampalam, S., Gordon, N., Beyond the Kalman Filter: Particle Filters for Tracking Applications, Artech House, Boston, MA, 2004.

·        Lee, H. K., Lee, J. G., “Fault-Tolerant Compression Filters by Time-Propagated Measurement Fusion,” Automatica, Vol. 43, No. 2, pp. 355-361, Feb. 2007.

·        Xu, B. L., Wu, Z. Y., Wu, Wang, Z. Q., “On the Cramér-Rao Lower Bound for Biased Bearings-Only Maneuvering Target Tracking,” IEEE Trans. on Signal Processing, Vol. 87, No. 12, pp. 3175-3189, Dec. 2007.

·        Mironovskii, L. A., “The Use of Analytical Redundancy,” Measurement Techniques, Vol. 50, No. 6, pp. 142-148, Feb. 2007.

·        Aloi, D. N., Alsliety, M., Akos, D. M., “A Methodology for the Evaluation of a GPS Receiver in Telematics Applications,” IEEE Trans. on Instrumentation and Measurement, Vol. 56, No. 1, pp. 11-24, Feb. 2007.

·        Petsios, M. N., Alivizatos, E. G., Uzunoglu, N. K., “Manuvering Target Tracking Using Multiple Bistatic Range and Range-Rate Measurements,” IEEE Trans. on Signal Processing, Vol. 87, No. 4, pp. 665-686, Apr. 2007.

·        on page 48 of Hue, C., Le Cadre, J.-P., Perez, P., Posterior Cramér-Rao Bounds for Multi-Target Tracking,” IEEE Trans. on Aerospace and Electronic Systems, Vol. 42, No. 1, pp. 37-49, Jan. 2006.

·        Chetouani, Y., “Fault Detection in a Chemical Reactor by Using the Standardized Innovation, Process Safety and Environmental Protection, Vol. 84, No. B1, pp. 27-32, Jan. 2006.

·        Gupta, V., Chung, T. H., Hassibi, B., Murray, R. M., “On a Stochastic Sensor Selection Algorithm with Applications in Sensor Scheduling and Sensor Coverage,” Automatica, Vol. 42, No. 2, pp. 251-260, Feb. 2006.

·        Hwang, D. H., Oh, S. H., Lee, S. J., Park, C., Rizos, C., “Design of a Low-Cost Attitude Determination GPS/INS Integrated Navigation System,” GPS Solutions, Vol. 9, No. 4, pp. 294-311, Nov. 2006.

·        Pulford, G. W., “Taxonomy of Multiple Target Tracking Systems,” IEE Proceedings-Radar, Sonar, and Communications, Vol. 151, No. 5, pp. 291-304, Oct. 2005.

·        Lee, T. H., Ra, W. S., Yoon, T. S., Park, J. B., “Robust Extended Kalman Filtering via Krein Space Estimation,” IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, Vol. E87A, No. 1, pp. 243-250, Jan. 2004.

·        Hagan, M. T., Demuth, H. B., De Jesus, O., “An Introduction to the Use of Neural Networks in Control Systems,” International Journal of Robust and Nonlinear Control, Vol. E87A, No. 1, pp. 243-250, Jan. 2004.

·        on page 2369 of Hernandez, M., Ristic, B., Farina, A., Timmoneri, L., “A Comparison of Two Cramér-Rao Bounds for Nonlinear Filtering with Pd < 1, IEEE Trans. on Signal Processing, Vol. 52, No. 9, pp. 2361-2370, Sep. 2004.

·        in references of Mutel, L. H., Speyer, J. L., “Fault-Tolerant GPS/INS Navigation System with Application to Unmanned Aerial Vehicles,Navigation: Journal of the Institute of Navigation, Vol. 49, No. 1, Spring 2002.

·        in references of Tichavsky, P., Muravchik, C. H., Nehorai, A., “Posterior Cramér-Rao Bounds for Discrete Time Nonlinear Filtering,IEEE Trans. on Signal Processing, Vol. 46, No. 5, pp. 1386-1396, May 1998.

·        in Siouris, G. M., Chen, G.-R., Wang, J.-R., “Tracking an Incoming Ballistic Missile using an Extended Interval Kalman Filter,IEEE Trans. on Aerospace and Electronic Systems, Vol. 33, No. 1, pp. 232-240, Jan. 1997.

·        in Napolitano, M. R., Chen, C. L., Naylor, S., “Aircraft Failure Detection and Identification using Neural Networks,AIAA Journal of Guidance, Control, and Dynamics, Vol. 16, No. 6, pp. 999-1009, 1998.

·        in Napolitano, M. R., Neppach, C., Casdorph, V., Naylor, S., Innocenti, M., Silventri, G., “Neural-Network-based Scheme for Sensor Failure Detection,AIAA Journal of Guidance, Control, and Dynamics, Vol. 18, No. 6, pp. 1280-1286, Nov.-Dec. 1995.

·        in Grejner-Brzezinska, D. A., Da, R., Toth, C., “GPS error modeling and OTF ambiguity resolution for high-accuracy GPS/INS integrated system,Journal of Geodesy, Vol. 72, pp. 626-638, 1998.

·        in Farina, A., “Target Tracking with Bearings-Only Measurements,Signal Processing, Vol. 78, No. 1, pp. 61-78, Oct. 1999.

·       in Ristic, B., Farina, A., Hernandez, M., “Cramér-Rao lower bound for Tracking Multiple Targets, IEE Proceedings-Radar, Sonar, and Navigation, Vol. 151, No. 3, pp. 129-134, Jun. 2004.

·        in Simandl, M., Kralovec, J., Tichavsky, P., “Filtering, Prediction, and Smoothing Cramér-Rao Bounds for Discrete Time Nonlinear Dynamic Systems,Automatica, Vol. 37, No. 11, pp. 1703-1716, Nov. 2001.

·       in Spall, J. C., Garner, J. P., “Parameter-Identification for State-Space Models with Nuisance Parameters,IEEE Trans. on Aerospace and Electronic Systems, Vol. 26, No. 6, pp. 992-998, Nov. 1990.

·       in Da, R., Lin, C. F., “A New Failure-Detection Approach and its Application to GPS Autonomous Integrity Monitoring,IEEE Trans. on Aerospace and Electronic Systems, Vol. 31, No. 1, pp. 499-506, Jan. 1995.

·        in Da, R., “Failure-Detection of Dynamical Systems with the State Chi-Square Test,AIAA Journal of Guidance, Control, and Dynamics, Vol. 17, No. 2, pp. 271-277, Mar.-Apr. 1994.

·        in Leung, H., Zhu, Z. W., “Performance Evaluation of EKF-based Chaotic Synchronization,IEEE Trans. on Circuits and Systems, Vol. 48, No. 9, pp. 1118- 1125, Sep. 2001.

·        in Bergman, N, Doucet, A., Gordon, N., “Optimal estimation and Cramér-Rao Bounds for Partial Non-Gaussian State Space Models,Annals of the Institute of Statistical Mathematics, Vol. 53, No. 1, pp. 97-112, Iss S I Mar. 2001.

·       in Mahapatra, P. R., Mehrotra, K., “Mixed coordinate tracking of generalized maneuvering targets using acceleration and jerk models,IEEE Trans. on Aerospace and Electronic Systems, Vol. 36, No. 3, pp. 992-1000, Jul. 2000.

·        in Park, S. T., Lee, J. G., “Improved Kalman Filter design for three-dimensional radar tracking,IEEE Trans. on Aerospace and Electronic Systems, Vol. 37, No. 2, pp. 727-739, Apr. 2001.

·        in Reece, S., “Nonlinear Kalman filtering with semi-parametric Biscay distributions,IEEE Trans. on Signal Processing, Vol. 49, No. 11, pp. 2445-2453, Nov. 2001.

·         in Sivananthan, S., Kirubarajan, T., and Bar-Shalom, Y., “Radar Power Multiplier for Acquisition of Low Observables using an ESA Radar,IEEE Trans. on Aero- space and Electronic Systems, Vol. 37, No. 2, pp. 401-418, Jan. 2001.

·        in Lee, T. H., Ra, W. S., Jin, S. H., et al, “Robust extended Kalman filtering via Krein space estimation,IEICE , No. 1, pp. 243-250, Jan. 2004. 

·        in Niu, R. X., Willett, P., Bar-Shalom, Y., “Matrix CRLB Scaling due to measurements of uncertain origin,IEEE Trans. on Signal Processing, Vol. 49, No. 7, pp. 1325-1335, Jun. 2001.

·      in Nabaa, N., Bishop, R. H., Solution to a Multisensor Tracking Problem with Sensor Registration Errors,  IEEE Trans. on Aerospace and Electronic Systems, Vol. 35, No. 1, pp. 354-365, Jan. 1999.

·      in Rizos, Chris, “Quality Issues in Real-Time GPS Positioning, International Association of Geodesy SSG 1.154, IUGG Congress, Birmingham, U.K., 18-29 July 1999.

·        in Jayakumar, M., Banavar, R. N., “Risk-sensitive filters for recursive estimation of motion from images,IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 20, No. 6, pp. 659-666, Jun. 1998.

·        in Mazor, E., Averbuch, A., Bar-Shalom, Y., et al,  “Interacting multiple model methods in target tracking: A Survey,IEEE Trans. on Aerospace and Electronic Systems, Vol. 34, No. 1, pp. 103-123, Jan. 1998.

·       in Benhaim, Y., “Optimizing Multi-hypothesis Diagnosis of Control-Actuator Failures in Linear Systems,AIAA Journal of Guidance, Control, and Dynamics, Vol. 13, No. 4, pp. 744-750, Jul.-Aug. 1990.

·        in Li, X. -R.,  Bar-Shalom, Y., “Performance Prediction of the Interacting Multiple Model Algorithm,IEEE Trans. on Aerospace and Electronic Systems, Vol. 29, No. 3, pp. 755-771, Jul. 1993.

·        in Campa, G., Fravdini, M. L., Seanor, B., et al, “On-line learning neural net- works for sensor validation for flight control system of a B777 research scale model,International Journal of Robust and Nonlinear Control, Vol. 12, No. 11, pp. 987-1007, Sep. 2002.

·       in Korbicz, J., Fathi, Z., Ramirez, W. F., “State Estimation Schemes for Fault-Detection and Diagnosis in Dynamic-Systems,”  International Journal of System Science, Vol. 24, No. 5, pp. 985-1000, May 1993.

·        in Ghil, M., Malanotterizzoli, P., “Data Assimilation in Meteorology and Oceanography,Advances in Geophysics, Vol. 33,  pp. 141-266, 1991.

·        in Hanan, K., Yahagi, T., “An iterative method for the identification of multi-channel autoregressive processes with additive observation noise,IEICE , No. 5, pp. 674-680, May 1996. 

·       in Liggins, M. E., Chong, C. Y., Kadar, I., et al, “Distributed fusion architectures and algorithms for target tracking,Proceedings of the IEEE, Vol. 85, No. 1, pp. 95-107, Jan. 1997.

·       in Wahnon, E., “A Min-Max Testing Approach to Failure-Detection and Identification,Lecture Notes in Control and Information Sciences, Vol. 144, pp. 487-496, 1990.

·        in Golovan, A. A., Mironovskii, L. A., “An Algorithmic Control of Kalman Filters,”  Automation and Remote Control, Vol. 54, No. 7, pp. 1183-1194, Jul. 1993.

·        in Gadzhiev, C. M., “Prediction of failures in linear-systems with the use of tolerance ranges,Measurement Techniques, Vol. 35, No. 8, pp. 851-896, Aug. 1992.

·        in Gadzhiev, C. M., “Prediction the Technical State of Dynamic Systems by a Kalman Filter Updating Sequence,Automation and Remote Control-Part 2, Vol. 54, No. 5, pp. 851-854, May 1993.

·        in Doerschuk, P. C., “Cramér-Rao Lower Bounds for Discrete-Time Nonlinear Filters,” IEEE Trans. on Automatic Control, Vol. 40, No. 8, pp. 1465-1469, Aug. 1995.

·        in Lu S., Doerschuk, P. C., “Performance Bounds for Nonlinear Filters,” IEEE Trans. on Aerospace and Electronic Systems, Vol. 33, No. 1, pp. 316-319, Jan. 1995.

·        in Zolghadri, A., Bergeon, B., Monison, M., “A Two Ellipsoid Overlap Test for On-line Failure Detection,” Automatica, Vol. 29, No. 6, pp. 1517-1522, 1993.

·        in Zolghadri, A.,  “An Algorithm for Real-Time Failure Detection in Kalman Filters,” IEEE Trans. on Automatic Control, Vol. 41, No. 1, pp. 232-240, Oct. 1996.

·        in Durrant-Whyte, H. F., Rao, B. Y. S., Hu, H., “Toward a Fully Decentralized Architecture for Multisensor Fusion,” Proceedings of 1990 Conference on Robotics and Automation, pp. 1331-1336, Cincinnati, OH, 13-18 May 1990.

·        in Blackman, S. S., Broida, T. J.,  “Multiple-Sensor-Data-Association and Fusion in Aerospace Applications,” Journal of  Robotic Systems, Vol. 7, No. 3, pp. 445-485, Jun.  1990.

·       in Roy, S., Hashemi, R. H., and Laub, A. J., “Square Root Parallel Filtering Using Reduced-Order Local Filters,” IEEE Trans. on Aerospace and Electronic Systems, Vol. 27, No. 2, pp. 276-289, Mar. 1991.

·       in Hong, L., “Centralized and Distributed Multisensor Integration with Uncertainties in Communication Networks,” IEEE Trans. on Aerospace and Electronic Systems, Vol. 27, No. 2, pp. 370-379, Mar. 1991.

·       in Makhoul, J., “Toeplitz Determinants and Positive Semidefiniteness,” IEEE Trans. on Signal Processing, Vol. 39, No. 3, pp. 743-746, Mar. 1991 (in particular, please see page 744, footnote and acknowledgement on page 748 for references to T. H. Kerrs professionally benign and positively supportive and cooperative interactions with the author of this work).

·        in Mertikas, S. P., Rizos, C., “On-line Detection of Abrupt Changes in the Carrier-Phase measurement of GPS,Journal of Geodesy, Vol. 71, pp. 469-482, 1997.

·        in Hagan, M. T., Demuth, H. B., De Jesus, O., “An introduction to the use of neural networks in control systems,International Journal of Robust and Nonlinear Control, Vol. 12, No. 11, pp. 959-985, Sep. 2002.

·        in Li, Y., Sundararajan, N., Saratchandray, P., “Stable neuro-flight-controller using fully tuned radial basis function neural networks,AIAA Journal of Guidance, Control, and Dynamics, Vol. 24, No. 4, pp. 665-674, Jul.-Aug. 2001.

·       in Brumback, B. D., Srinath, M. D., “A Fault-Tolerant Multisensor Navigation System-Design,IEEE Trans. on Aerospace and Electronic Systems, Vol. 23, No. 6, pp. 738-756, 1987.

·       in Brumback, B. D., Srinath, M. D., “A Chi-Square Test for Fault-Detection in Kalman Filters,” IEEE Trans. on Automatic Control, Vol. 32, No. 6, pp. 532-554, June 1987.

·       in Uwe D. Hanbeck, “Recursive Nonlinear Set-Theoretic Estimation Based on Pseudo-Ellipsoids,” Proceedings of the IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems, pp. 159–164 (MFI2001), Baden–Baden.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.304.8080  
https://www.researchgate.net/publication/3955109_Recursive_nonlinear_set-theoretic_estimation_based_on_pseudo_ellipsoids 
https://core.ac.uk/display/22665895 
https://core.ac.uk/display/24506648
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.70.3779
Their patent abandoned by Siemens AG (perhaps because of prior art: me): https://patents.google.com/patent/US20060234722A1/en

·       S. Sang, R. Wang, Z. Hong, "Distributed Fusion Tracking Estimation under Range-Only Measurement," 
IEEE Access, 2022
This paper concentrates on the distributed fusion estimation problem for range-only 
target tracking system with unknown but bounded noises, where the linear and 
nonlinear motion models are both considered. A kind of nonlinear transformation is 
used to convert the nonlinear distance measurement model into a linear one, which 
eliminates the corresponding linearization errors in the design of estimation error 
system. In spite of the transformed measurement noise becomes more complicated
…It also references:

      Kerr, T. H., Streamlining Measurement Iteration for EKF Target Tracking,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 27, No. 2, pp. 408-421, Mar. 1991.

 Numerous prior historical citations to our work are also available upon request (some others being listed on our Home Page).

Also see: https://scholar.google.com/citations?user=UjaYY4EAAAAJ&hl=en

-https://academic.microsoft.com/#/detail/2424976702  
-https://www.researchgate.net/profile/Thomas_Kerr_Iii
 
-https://scicomp.stackexchange.com/users/27180/thomas-h-kerr-iii 
-https://blogs.mathworks.com/headlines/2016/09/08/this-56-year-old-algorithm-is-key-to-space-travel-gps-vr-and-more/ , where some of our published work is displayed.

Recall that we go through the detailed epsilon-delta arguments so that you dont have to (by our bending over backwards to explain things in simple terms that are understandable up and down the line at all levels of sophistication and interests).

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